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dc.contributor.authorJedwanna, Kriten_US
dc.contributor.authorChanintornthep, Weerathepen_US
dc.date.accessioned2022-04-24T05:19:33Z
dc.date.available2022-04-24T05:19:33Z
dc.date.issued2022-04-24
dc.identifier.issn2651-1096
dc.identifier.urihttp://repository.rmutp.ac.th/handle/123456789/3806
dc.descriptionRMUTP Research Journal, Vol. 15, No. 1, January-June 2021, pp 193-214en_US
dc.description.abstractAccurate, efficient and robust travel time prediction is crucial to the development of advanced traveler information systems for providing route guidance information. To achieve this goal, this paper proposed a travel time prediction through the matching of the current speed interval pattern to that in a historical database. Speed intervals, instead of speeds, are considered in this study to simplify the structure of matching patterns for improving matching efficiency. In this study, speed interval patterns are defined by sets of link speed intervals that are either spatially or temporarily correlated with the link considered. With the speed interval patterns, the algorithm is developed for searching the historical pattern(s) that is/are the closest match with the current one. Then, link speeds from these matched patterns are combined for travel time prediction. By using the GPS probe taxi data, which the collected speeds are aggregated in every 5 minutes, the proposed travel time prediction system is implemented in Bangkok. With the speed data from probe taxi, this paper has chosen four links/paths with different geometric and flow characteristics for testing the performance of the proposed travel time prediction system. From these tests, it is found that the optimal speed interval pattern should include: 1) speeds of the studied link within three preceding time intervals and; 2) speeds of links in the first connection level of the studied link. Also, while the computational time is capable of real-time application, the proposed prediction algorithm is more accurate under uninterrupted flow conditions.en_US
dc.description.sponsorshipRajamangala University of Technology Phra Nakhonen_US
dc.language.isoenen_US
dc.subjectAlgorithmsen_US
dc.subjectอัลกอริทึมen_US
dc.subjectTravelen_US
dc.subjectการท่องเที่ยวen_US
dc.subjectTravel timeen_US
dc.subjectเวลาการเดินทางen_US
dc.subjectSpatiotemporal Correlationen_US
dc.subjectสหสัมพันธ์เชิงพื้นที่en_US
dc.titleReal-time travel time prediction algorithm using spatiotemporal speed interval patterns matchingen_US
dc.typeJournal Articlesen_US
dc.contributor.emailauthorkrit.j@rmutp.ac.then_US
dc.contributor.emailauthorarit@rmutp.ac.then_US


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